
import pandas as pd
import glob, folium, branca, json
import numpy as np
import matplotlib.pyplot as plt

import holoviews as hv
import panel as pn
import panel.widgets as pnw

hv.extension('bokeh')


print(np.datetime64('now'))

2021-02-18T00:28:40


# PUT EVERY COUNTRY REPORTS IN ONE DATAFRAME
files = glob.glob('data/install*country.csv')
files.sort()
ds=pd.DataFrame()
for f in files:
    ds = pd.concat([ds,pd.read_csv(f,encoding = 'utf-16')])
ds = ds.reset_index()    
ds = ds.drop(columns=['index','Daily Device Upgrades','Total User Installs','Active Device Installs','Install events','Update events','Uninstall events'])
ds['Date']=pd.DatetimeIndex(ds['Date'])
ds['WO-ui']=ds['Daily User Installs'].cumsum()
ds['WO-di']=ds['Daily Device Installs'].cumsum()
ds['WO-uu']=ds['Daily User Uninstalls'].cumsum()
ds['WO-du']=ds['Daily Device Uninstalls'].cumsum()


countries = np.unique(ds['Country'][~ds['Country'].isna()])
for country in np.unique(ds['Country'][~ds['Country'].isna()]):
    ds[country+'-di']=ds[ds['Country']==country]['Daily Device Installs'].cumsum()
    ds[country+'-ui']=ds[ds['Country']==country]['Daily User Installs'].cumsum()
    ds[country+'-du']=ds[ds['Country']==country]['Daily Device Uninstalls'].cumsum()
    ds[country+'-uu']=ds[ds['Country']==country]['Daily User Uninstalls'].cumsum()
ds = ds.fillna(method='ffill')
ds = ds.fillna(0)
ds.tail()


A2 = pd.read_csv('A2codes.csv',index_col=1)
A2i = pd.read_csv('A2codes.csv',index_col=0)

labels = [A2['Name'][x] for x in np.hstack([countries,'WO'])]

label = pnw.Select(name='Country', value='World', options=labels)
ptype = pnw.Select(name='Type', value='Install', options=['Install','Uninstall'])

@pn.depends(label.param.value,ptype.param.value) 
def create_figure(label,ptype):
    code = A2i['Code'][label]  
    if code != 'WO':
        dsi = ds[ds['Country']==code]
    else:
        dsi=ds
    
    hv_data = hv.Table(dsi, ['Date'])    
    p1 = hv_data.to.curve(['Date'], [code+'-u'+ptype[0].lower()],label='Users').opts(color='r')
    p2 = hv_data.to.curve(['Date'], [code+'-d'+ptype[0].lower()],label='Devices').opts(color='b')      
    p = p1*p2
    p.opts(hv.opts.Curve(width=1000, height=400,show_grid=True),
           hv.opts.Overlay(legend_position='top_left'))
    t = hv.Table(dsi[['Date',code+'-ui',code+'-di',code+'-uu',code+'-du']])
    t.opts(hv.opts.Table(width=500,height=380))
    
    return p+t
    

widgets = pn.WidgetBox(label, ptype, width=170)
pn.Row(widgets, create_figure)


df = pd.DataFrame(ds.groupby('Country').sum()['Daily User Installs'])
color_scale = branca.colormap.linear.viridis.scale(0,20)
map_dict = df.to_dict()

def get_color(feature):
    value = map_dict['Daily User Installs'].get(feature['properties']['ISO_A2'])
    if value is None:
        return 'white' # MISSING -> white
    else:
        #print(feature['properties']['ADMIN']+' : '+str(value))
        return color_scale(value)

m = folium.Map(
    location = [0, 0], 
    tiles="cartodbpositron",
    zoom_start = 2
)

folium.GeoJson(
    data = 'countries.json',
    style_function = lambda feature: {
        'fillColor': get_color(feature),
        'fillOpacity': 0.7,
        'color' : 'None',
        'weight' : 1,
    }    
).add_to(m)
m.add_child(color_scale)
m

	Date	Package Name	Country	Daily User Uninstalls	WO-ui	WO-di	WO-uu	...	SV-uu	UA-di	UA-ui	UA-uu	US-di	US-ui
1017	2021-02-14	com.kb.android.argo	MY	0	77	82	25	...	1.0	1.0	1.0	2.0	7.0	5.0
1018	2021-02-14	com.kb.android.argo	NO	0	77	82	25	...	1.0	1.0	1.0	2.0	7.0	5.0
1019	2021-02-14	com.kb.android.argo	RU	2	77	82	27	...	1.0	1.0	1.0	2.0	7.0	5.0
1020	2021-02-14	com.kb.android.argo	SI	0	77	82	27	...	1.0	1.0	1.0	2.0	7.0	5.0
1021	2021-02-14	com.kb.android.argo	US	0	77	82	27	...	1.0	1.0	1.0	2.0	7.0	5.0

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